“AI’s data inputs, deployments and spillovers across
“The pervasive use of AI in our daily lives and its impact on people, society and the environment makes AI a socio-technical field of study.” Francesca Rossi, IBM Fellow and AI Ethics Global Leader, AAAI
The widespread influence of artificial intelligence (AI) is poised to reshape social roles, work dynamics, governance and global equity. Unclear trends highlight the urgent need for fore-sight and flexible, adaptive governance.
AI inequality vs AI inclusion
We are still in the early stages of AI’s global spread. One scenario envisions AI amplifying existing patterns, including inequalities. The concentration of AI development in a few countries and companies echoes the recent history of the internet. Accelerated scientific progress and productivity gains could accrue sooner for those already at the forefront of AI development and adoption, widening existing gaps and deepening power imbalances.
However, cheaper and more accessible AI technologies could also spread globally, shaping many different aspects of life. Already, AI is being used to help draft laws, diagnose diseases and support learners around the world. Risks also lurk in such productive applications, from reinforced biases to misleading diagnoses and cognitive passivity. Opportunities and risks will be amplified by technology’s spread.
Both these scenarios could happen in parallel, with AI concentration accompanied by AI mushrooming. What seems clear is that AI’s expanding development, deployment and use will continue to expand across borders, fuelled by investment, optimism and anxiety.
Destabilising existing orders
Physicist and computer scientist John Von Neumann argued that such technological expansion destabilises existing orders, testing the limits of geography, existing relationships and political organisations with a cascading wave of technology-charged change.
New AI-related industries are emerging, just as existing ones accelerate, scale and automate. The International Monetary Fund (IMF) estimates that 40% of global employment is exposed to AI, implying many winners and losers. The societal impacts of such shifts, and many others, will also unfold amidst geoeconomic and geopolitical competition over AI’s supposed ability to boost countries’ wealth and power.
Many of these implications can be addressed at the company or national level. Yet, AI’s data inputs, deployments and spillovers cross borders, calling for international cooperation.
The role of international cooperation
Given the inherent uncertainty over when and how such dynamics will evolve, Von Neumann posited that only day-to-day, or perhaps year-to-year, opportunistic measures could ensure human survival and flourishing: ‘a long sequence of small, correct decisions.’
This year, the United Nations is set to establish an Independent International Scientific Panel on AI and a Global Dialogue on AI Governance. Such measures will promote scientific understanding of AI’s risks, opportunities and impacts to support more effective AI policymaking and help countries collaborate on how they are governing AI. It will also consider financing options for AI capacity-building. AI may be a powerful technology, but it is human patience, flexibility and intelligence that remain our best hope for navigating the global expansion of AI for the common good.
“The great benefit of artificial intelligence is that it’s an extraordinarily accessible tool,” says Andrew Pyne, Head of Growth at tmc3, a consultancy providing cybersecurity and data protection services to the public and private sector. “Unfortunately, this is also its greatest risk.”
Which is why organisations must take a proactive approach to AI security and governance, tapping into specialist advice from a trusted partner and implementing solutions and guardrails that offer best-inclass, built-in protection.
Why AI needs responsible deployment
While Pyne doesn’t want companies and institutions to be afraid of AI, he warns that they shouldn’t underestimate the harm it can cause if left unchecked. There is a (misleading) argument that security protocols act as a brake on AI innovation and prevent it from reaching its full social and commercial value. Pyne insists the reverse is true. “It’s like a car with good safety features,” he says. “If you’re wearing a seatbelt, you’re able to drive faster because you’re safer. Security is AI’s seatbelt.”
Organisations using AI must protect themselves with good security and governance. These are safeguards that can actually unlock — not block — the technology’s full potential.
consumer usage, which will save billions on the grid upgrade. The pace of change is so exciting. It’s going to solve humanity’s biggest challenges.”
As exciting as this potential is, if your organisation is planning to launch a generative-AI pilot, you should ensure that proactive safety measures are in place, including good cyber hygiene practices. “That can be as simple as staff training,” says Lloyd. “Don’t just forbid your people from using AI tools in a certain way — explain why. In our experience, staff don’t want to cause damage to their organisation but may not understand the consequences of their actions.”
Don’t just forbid your people from using AI tools in a certain way — explain why.
The fact is that people in your organisation are going to use AI tools. “They probably already are,” notes Pyne. “So, you have three options. You can ignore it. You can try to block your people from using it. However, they’ll just find ways around that — or you can get on board with it and make sure it’s deployed safely.”
Revolutionary tech that will change lives and industries
Options one and two aren’t options at all, he admits, because the AI genie is now well and truly out of the bottle. Anthony Lloyd, Principal Cyber Technologist at tmc3, agrees. “Secure AI is going to change lives and industries,” he says. “For example, it’s going to deliver better time management for clinicians and revolutionise patient outcomes in the NHS. In the energy sector, it’s going to fundamentally alter the way we understand
Also, Lloyd warns, if you’re going to integrate AI into your internal applications, you need to test it thoroughly to identify vulnerabilities. “That sounds like an obvious thing to say,” he agrees. “Yet, every month, we hear of application security being compromised. So, it’s vital to actively employ security controls.”
UK businesses will be affected by new EU regulations
There’s another pressing reason why companies should ensure they are using AI in a safe, legal and ethical way. Last year, the European Union Artificial Intelligence Act — the world’s first major regulatory framework for AI — came into force. Its different provisions apply in stages (including some milestone obligations in 2025), but it will be fully applicable by August 2026. Complying with it now offers an early opportunity to win trust and cross-border business. “If you’re a British company wanting to trade with the EU, then the Act will affect you,” stresses Pyne. Most organisations can’t hope to understand the AI threat landscape on their own, which is why collaboration with a trusted cybersecurity partner is critical. “This technology is continually evolving, making it hard to keep up with the risks it poses,” says Pyne. “So, engage with people who make that job their sole focus.”
The UK stands at a crucial juncture, poised to either lead or lag in the burgeoning era of artificial intelligence.
Acknowledged as a significant player on the global stage, boasting the third-largest AI market, the UK faces a pressing need to translate its potential into tangible progress.
The Labour government’s AI Opportunities Action Plan explicitly recognises the urgency of accelerating AI adoption to fuel economic growth and societal advancement — or face the possibility of the nation falling behind the rapid strides made by global powerhouses like the USA and China.
The UK’s AI readiness challenge Dark Matter, in association with Hewlett Packard Enterprise (HPE), is investigating the UK’s preparedness to embrace the AI era and addresses the challenges — and considerable opportunities — that UK businesses and government bodies face as they navigate this largely uncharted AI territory.
From digital sovereignty, environmental sustainability, to infrastructure and talent pipelines, Dark Matter’s initiative focuses on deeper structural questions that need answers.
The stakes are high and the answers, as outlined by experts from across UK PLC, are not straightforward.
Assuming the UK goes forward in building a sovereign AI platform, let’s call it a national grid of AI, one that makes AI accessible for all, that would be a great outcome for UK citizens, business, talent and the economy.
Building the UK’s AI backbone at home
One of the most pressing concerns raised by industry experts is the concept of sovereign AI. This encompasses not only data residency within the UK but also the development of domestic AI capabilities to reduce reliance on foreign providers and ensure national resiliency.
The UK Government has promised to expand the country’s sovereign AI computing capacity by at least 20 times by 2030 and establish dedicated AI Growth Zones to accelerate the build-out of AI infrastructure. Benedict MaconCooney, Chief Policy Strategist at the Tony Blair Institute, emphasises that the UK needs to “build very, very strong AI capabilities at home” to exercise its own power in the modern economy.
Karl Havard, CCO at Nscale, shared his view on the UK’s ambitions: “Assuming the UK goes
forward in building a sovereign AI platform, let’s call it a national grid of AI, one that makes AI accessible for all, that would be a great outcome for UK citizens, business, talent and the economy.”
UK AI sovereignty challenge
However, experts point to the challenge that much of the country’s data infrastructure still sits with foreign providers like AWS, Azure and Google Cloud — a juxtaposition to the sovereign ambition. As Professor Gopal Ramchurn, CEO of Responsible AI UK notes:
“The UK’s approach to adopting AI and deploying it at scale has largely been dictated by views from the US.”
“The traditional hyperscalers, because they’re US-based, cannot be UK sovereign. Sovereignty means the infrastructure, the data and the economic benefit stay in the UK. We need to build the belief that we can do this ourselves,” says Havard.
While the concept of sovereign AI was once a fringe concern, it’s fast becoming mainstream. Amid rising cyber threats and geopolitical instability, there’s growing awareness about the importance of maintaining control over public data when training AI models. There are valid concerns about data confidentiality, training practices and the potential misuse of proprietary information.
Industry experts emphasise that without a
crisis,” Professor Ramchurn says. “It’s very hard to know who’s a real expert, who we can trust to give us the right expectations about AI, to give us the right predictions about the impact of AI.”
Havard adds: “We need a common purpose and an orchestrating layer to be able to help everybody come together and collaborate and then show the rest of the UK the results and be proud of them. We need to say to the public, we can lead the world and here’s a set of results to prove it.”
resilient, hybrid infrastructure rooted in UK soil, ambitions for long-term AI leadership may fall short.
Skills, trust and public confidence
The investigation also highlights the skills gap that continues to challenge the UK’s AI ambitions. While AI Engineering and Data Science roles are growing in demand, there remains a shortage of skilled professionals to meet current and future needs. Lifelong learning initiatives are still limited, and public trust in AI remains a work in progress.
On the issue of skills, Matt Harris, SVP & Managing Director UKIMEA at HPE, highlights the importance of developing UK AI skills and the potential this provides the nation: “I actually think about national competitiveness when it comes to sovereignty. I think about the skills that are going to be potentially built on our shores, which means that we become an AI exporter.”
Industry experts emphasise that without a resilient, hybrid infrastructure rooted in UK soil, ambitions for long-term AI leadership may fall short.
However, to grow skills, you need trust. The trust deficit isn’t abstract, as it affects real decisions from health to finance to national security, where the deployment of AI could reshape lives and institutions. “I think, right now, we have a trust
Experts suggest that only through responsible education, transparent frameworks and skilled oversight can trust be earned and maintained.
Learning from the past
The investigation draws a sharp line between AI and the last technological transformation the UK embraced wholesale: cloud computing and history serve as a cautionary tale. Not all migrations delivered on the public cloud’s promise of efficiency and flexibility. For some, the lack of planning led to spiralling costs, security issues, and a difficult path to repatriation.
Abdi Goodarzi, Head of GenAI Products at Deloitte, cautions, unlike the mistakes made during the cloud boom, “there’s more at stake” with AI. “AI has gone through a different curve. The reason being is AI needs a lot of foundational elements to be in place, data and computing.”
AI must be purposeful and value-driven Goodarzi further suggests that without the right data, computing and governance in place, there could be mistakes, but on a much larger scale. AI-driven technological transformation needs forethought, considered infrastructure and a roadmap that accounts for unintended consequences.
AI implementation must provide genuine value and avoid becoming an exercise in simply adopting AI for AI’s sake. It’s easy to get caught up in the hype surrounding AI, but organisations must define and fund use cases based on a clear understanding of the potential impact on citizens, return on investment and outcomes.
As Goodarzi goes on to say, many companies are engaging in proof of concepts and pilots, highlighting the need to first figure out viable applications. The ultimate goal should be tangible benefits, not just the deployment of AI itself.
Unlocking AI responsibly
HPE is committed to unlocking AI for the UK in a responsible and purposeful way, backing infrastructure, strategy and skills development that can scale sustainably and serve the public good.
They are supporting Dark Matter in asking the critical questions and highlighting to the public that AI is not a switch to be flipped without careful consideration and thought-through strategies. If the UK is serious about leading in AI, that journey needs to begin with truth, not hype.
AI PCs can boost productivity across multiple roles by automating tasks in growing areas such as finance, HR, legal and marketing to enable smarter decisions, faster workflows and more strategic focus.
Devices introducing AI-based workflows are creating more intelligence for tailored experiences based on roles within an organisation. Whether it’s automating everyday tasks, streamlining operations, empowering employees to focus on what truly matters, or giving IT teams greater control and insights, AI PCs are not just a tech upgrade — they’re a strategic advantage.
Transforming SME business
Experts foresee the integration of AI technologies as transforming SME business operations (small and medium enterprises) in areas such as addressing skills gaps and human-machine collaboration. Industry figures suggest that 86% of employers expect AI and information processing technologies to transform their business by 2030, with this expectation higher in Financial Services (97%) and Electronics (95%) sectors.
While a barrier to AI adoption is the lack of skills to support it, an opinion shared by 50% of executives worldwide, 77% of surveyed employers plan to reskill and upskill their existing workforce to work more effectively alongside AI by 2030. Meanwhile, GenAI is seen as augmenting, rather than replacing, human work and demonstrates strengths in data mining, machine learning applications, multi-lingualism and can assist in summarising complex information, drafting text,
performing calculations, and translation.
“GenAI is enhancing a range of employee skills that require nuanced understanding and problemsolving,” says Jen Larson, General Manager of Intel’s Commercial PC business. “It makes tasks easier and empowers employees to have access to increased levels of business intelligence, and that can have a profound impact on the quality of their work.”
Business benefits of AI solutions
Against this backdrop, AI PCs are becoming more accessible to SMEs as manufacturers expand production and introduce options at various price ranges. It is not only creative roles such as art designers or copywriters that boost their productivity by leveraging AI applications on AI PCs. Back-office functions like finance, legal and HR can also benefit.
Finance professionals can build rigorous financial models and presentations, drive key strategic decisions and deliver high-value work rather than spending time on mundane tasks;
HR professionals can use AI tools for workforce planning, talent acquisition, improving candidate identification, better communication, learning and development and performance management; within legal departments, tasks like document review, contract analysis and legal research can be automated, allowing lawyers to focus on more complex work.
Dynamic gamechanger
Industry expert Massimiliano Rossi, who is Vice President of the Product Business Unit in Acer’s EMEA team, said organisations of all sizes, from large enterprises to small and mid-sized companies, will benefit from AI PCs.
“To support the AI transformation, the adoption of AI PCs is essential to revolutionise the workplace experience, allowing employers to reskill and upskill their teams,” he explains. “From brainstorming new ideas to analysing data more efficiently, the potential of AI PCs continues to grow.”
With a long battery life, even while using demanding AI-based apps, he believes AI PCs can be a gamechanger for different roles in SMEs. “For example, knowledge workers are able to enjoy smart task automation and real-time analytics of
sales and inventory dashboard, freeing up time to focus on more strategic areas and have a more personalised work experience based on their roles and tasks. Sales and marketing is another great example where we see the power of AI PCs enhance content creation development and generate strategic customer insight.”
Intelligent workflows
There have been significant changes observed in the past year following the launch of AI PCs and the continuous evolution of AI technology in performance, efficiency and security. “One of the most noticeable shifts,” says Rossi, “is how AI PCs have moved from a futuristic concept to a practical, beneficial tool that is significantly impacting our daily computing experience.
“This includes scaling AI PCs to a broad set of form factors from the notebook to desktop to mobile workstations, giving customers a choice based on what makes sense to their employees and helping create an important competitive advantage. It’s the ability to work smarter and solve problems faster.”
Strong partnership
Rossi points to a strong partnership between Acer and Intel in delivering an innovative portfolio of AI PCs, coming with NPU power designed to efficiently handle AI tasks and Copilot+ PCs, which require more than 40 TOPS (Trillion Operations Per Second). This new class of Windows PCs are built with powerful AI capabilities that run directly on devices — enabling even faster, smarter and more personalised experience for SMEs.
The AI solutions automate repetitive tasks and can lead to improved decision-making and streamlined workflows, resulting in cost savings and enhancing employee experience and retention. “With limited resources, AI PCs can help SME staff work more efficiently and intelligently – regardless of their role or function,” says Rossi.
Acer’s commercial portfolio includes AI PCs
and Copilot+ PCs powered by Intel® Core™ Ultra processors with Intel vPro®, which is a dedicated platform for business. “The introduction of the AI PC is an important inflexion in our PC journey because Acer and Intel are driving a new era of intelligent experiences and also delivering on the fundamentals of a great PC experience,” he adds.
Extraordinary energy efficiency
Larson says Acer’s Copilot+ PCs with Intel Core Ultra 200V series processors offer extraordinary energy efficiency. These devices leverage NPUs with more than 40 TOPs and are combined with Intel’s Central Processing Unit (CPU) and Graphical Processing Unit (GPU) to deliver three dedicated AI engines. This provides unmatched processing speed and efficiency.
Users gain new levels of PC efficiency that make AI workflows like collaboration effortless with up to 40% lower power consumption.*
Security enhancement
A major advancement, she continues, is in AI security. “In a rapidly evolving threat landscape, Intel is using PC hardware to augment security software to deliver comprehensive protection.”
“This includes new ways to work with ISVs (Independent Software Providers) on security solutions that take advantage of Intel’s AI-hardware foundation to deliver faster threat detection for customers. This includes detecting and blocking a wide range of emerging cyber threats, including deepfakes, phishing attempts and firmware attacks,” says Larson.
Steps toward implementation
To fully capitalise on the advantages of AI PCs, organisations should take a strategic approach. They should:
• Identify key areas where AI can add value, such as operations and customer service;
• Regularly assess the performance of AI systems to ensure they meet business goals;
• Provide training programs to enhance employees’ understanding of AI technology and applications;
• Foster a culture of innovation by encouraging a mindset of experimentation within an organisation.
“SMEs that delay plans to embrace AI technology may fall behind their competition in terms of efficiency, flexibility and growth opportunities,” notes Larson. “In contrast, those that proactively adopt AI PCs are experiencing significant gains in productivity and security, enabling faster and easier access to new business opportunities.”
Test the waters
SMEs can “test the waters” with a pilot installation before scaling AI PCs deployments as employees become more comfortable with the transition. Acer and Intel say customers moving to AI PCs and Copilot+ PCs are generating better business outcomes that give them a competitive advantage, whilst also increasing employee satisfaction.
Rossi concludes: “We are actively collaborating with key business partners in adopting AI onto their operations. Some have shared with us that the future-proof AI PCs bringing in AI-driven solutions to optimise their workflow are empowering employees to handle complex workloads easier and faster.”
To successfully transition to AI solutions, SMEs should choose appropriate AI PCs to fit their business needs.
Acer and Intel believe SMEs have a significant opportunity to use AI PCs and Copilot+ PCs as a strategic productivity tool to gain a competitive advantage and that now is the time to upgrade, particularly with support ending for Windows 10.
“AI PCs and Copilot+ PCs can positively position small and midsize enterprises for the future while generating immediate value,” says Massimiliano Rossi. “But they should choose Copilot+ PCs with efficient performance to help them deal with business tasks and operations, as Copilot+ PCs are the fastest, most intelligent Windows PCs.”
Acer’s TravelMate series offers a wide range of options, including AI PCs and Copilot+ PCs, catering to the diverse needs and budgets of SMEs. Equipped with Intel® Core™ Ultra processors and Intel vPro®, they enable advanced AI experiences, accelerated performance and multilayer protections and store data locally to the device, enabling organisations to better safeguard their data.
Intel AI PCs use the power of three AI engines: the CPU for lightweight tasks, GPU for media and 3D rendering and the NPU for dedicated AI workloads, offering app developers flexibility and optimal performance. Intel’s Core Ultra 200V series, for example, offer an impressive 48 NPU TOPS and a combined 120 platform TOPS across the CPU, GPU and NPU. AI PCs and Copilot+ PCs with Intel vPro® enable IT professionals to create a more proactive security and PC management posture with real-time threat detection.
“The added layer of intelligence helps detect and prevent threats and enables IT be more agile in managing their PC fleets to avoid outages,” says Jen Larson.
AI futures: AI is shaping our world, but who’s shaping
Learn how AI and tech can empower diverse young voices through inclusive tech education, building a future where everyone can feel a sense of belonging and lead.
The new inevitability is that artificial intelligence is rapidly shaping our world, whether you’re ‘in’ or not.
Missing voices
Currently, AI is created, developed, tested, deployed and regulated in exclusive circles, by a narrow demographic — an artefact of the wider ethnicity, gender, disabled people, plus regional and socioeconomic diversity gaps in tech. The voices of many are deemed irrelevant or missing. There’s a social imperative — and societal and business case — to intentionally ensure AI is created by, and for, everyone.
In today’s tech-driven workplaces, we’re witnessing an unprecedented rise in AI-powered surveillance and productivity tools.
As many as 85% of employers now deploy some form of surveillance software, fundamentally altering the relationship between workers and management in ways we’re only beginning to understand. As someone focused on technology and inclusion, I’m most concerned by the ‘transparency asymmetry’ these systems create — where employees are highly visible, but management decisions remain opaque. This imbalance disproportionately harms those already marginalised in workplace culture.
When companies implement keystroke logging, screen captures, and even biometric tracking, they’re not simply measuring productivity; they’re potentially encroaching on privacy and undermining trust. The human complexity of work — with its need for creative thinking, collaboration and occasional downtime —cannot be captured through digital activity metrics alone. Consider recruitment algorithms trained on historical hiring data. Without careful oversight, these systems may perpetuate patterns of exclusion, overlooking qualified candidates from underrepresented groups.
Ensuring tech reaches all
The tech careers education and social mobility charity Tech She Can is on a mission to reach all, in classrooms and with workplace experiences across the UK. Backed by business, our free schools’ programme (Tech We Can) for boys and girls brings tech roles to life, showing children relatable industry role models and linking their passions to tech.
We are raising aspirations and opening doors. It is vital, inspirational and emotional work. It has the power to change life outcomes and, ultimately, the technologies we all use. We are racing to meet demand: our virtual school’s assembly on AI inspired and educated 40,000 children in one day; and our inaugural annual AI Summit in partnership with Accenture invited 250 twelve-year-olds from the North West to imagine AI futures — built by them.
Inclusion is a choice
We must all choose to invest in and expand inclusive tech education that truly delivers results. The UK cannot afford — socially or economically — to ignore the curiosity, energy, creativity, talent and unique experiences of all.
Perhaps most troubling is how these systems risk amplifying existing inequalities. Neurodivergent staff or those with disabilities may find themselves penalised by systems designed with normative assumptions about productivity. When career progression becomes tied to these metrics, we create new barriers to advancement for already underrepresented groups. However, these technologies also offer potential benefits when thoughtfully implemented. They can identify patterns of exclusion that human managers might miss, standardise evaluation criteria and reduce the impact of individual bias in decision-making.
Prioritise ethics over optimisation
Moving forward, organisations must establish clear boundaries around what will be monitored, with transparent communication about data usage at all points of the employees’ career lifecycle. Regular algorithmic impact assessments focused on effects on underrepresented groups are essential, as are accessible appeal mechanisms allowing employees to challenge automated decisions.
The pace at which these tools are being developed has often created a two-dimensional approach to workplace challenges, leaving the third dimension of ensuring equity and transparency as an afterthought. As we navigate this new landscape, we must balance technological capabilities with human dignity, ensuring that in our pursuit of optimisation, we don’t lose the humanity that drives innovative and meaningful work.
The future of AI cannot happen without women: why innovation depends on gender equity
A future led by diverse tech teams is essential. To unlock AI’s full potential, the UK must enable women in tech. Gender equity in tech is not just a moral imperative but economically and socially necessary.
Despite decades of progress, women remain woefully underrepresented in the UK’s technology workforce. Only 23% of people working in STEM roles are female, and a mere 5% hold leadership positions in the tech industry.1 The AI sector is even more skewed, with women making up just 22% of the workforce globally.2
Girls in tech lack role models and support
The imbalance is not for lack of talent or ambition; girls perform as well as, or better than, boys in school STEM subjects, but lack confidence and visible role models to pursue these careers. The result? The UK is competing in the global tech race with one hand tied behind its back.
Why equity is vital in AI
AI is rapidly transforming every sector, from healthcare and finance to education and public services. Policy Connect’s forthcoming report, ‘Skills in the Age of AI’ (to be published in June 2025), reveals that without embedded equity, inclusion and diversity within the fabric of innovation, emerging technology will only reflect and amplify existing biases.
AI trained on data that underrepresents women can produce discriminatory outcomes, from flawed hiring algorithms to biased medical diagnostics.3
Gender-balanced teams are more likely to anticipate and correct these biases, ensuring AI works for everyone, not just a privileged few.4
Trust gaps hinder AI adoption
The key barrier to adopting and experimenting with AI systems is clear: training opportunities and courses are abundant. They aim to reskill and upskill across the sector. Yet, key barriers such as technology trust gaps and systemic pressures like bias and underrepresentation within AI development have persisted despite the Government’s enthusiastic call to establish the UK as a leader in AI adoption and use.
‘Skills in the Age of AI’ is a call to action for a pathway to ensure wider participation and usage of tech across underrepresented and marginalised groups across the nation.
An AI-ready team blends technical acumen with adaptability, communication skills and ethical awareness.
Everybody is talking about AI, but what about the people behind it? With the AI skills gap widening, a targeted STEM workforce consultancy can help businesses stay ahead.
Artificial intelligence is often framed as a technological revolution, but its true potential lies in the hands of people.
The human factor in AI success Technology doesn’t implement itself, and algorithms don’t deploy at scale without the engineers, data scientists and domain experts who can make it happen. “It’s not just about coding models,” says SThree CEO Timo Lehne. “It’s about designing systems that are usable, fair and future-ready.”
AI is only as powerful as the teams behind it. These teams need to be grounded in interdisciplinary collaboration and include not just technologists but also communicators, change managers and ethical thinkers.
Encouraging acceptance
AI is commonly seen as a threat to existing job roles. This, however, could not be further from the truth.
AI is reshaping roles, reducing repetitive tasks and allowing skilled professionals to focus on more strategic and creative work.
“If AI is perceived as a threat, resistance is likely to stall progress. It is essential to involve and inform your people before rolling out AI programmes to encourage their understanding and support,” explains Sarah Mason, Chief People Officer.
In healthcare, for example, AI is helping to analyse medical data more quickly, but the final decisions still rest with human experts and clinicians. By equipping and supporting your current and future workforce with the right skills and values, you ensure AI becomes a tool for empowerment, rather than exclusion.
Future-proofing your workforce While organisations are racing to integrate new technologies, something is all too often overlooked: people. While ambition is high, the talent pool is tight. Businesses need to find the right mix of skills, from machine learning to data ethics to systems integration and cloud architecture. With roles evolving fast, yesterday’s job specs may not cut it tomorrow.
“Technical roles like data scientists, machine learning engineers and AI ethicists are vital, but equally important are roles that ensure AI has real-world impact: project managers, domain experts in life sciences or engineering, and even behavioural experts,” says Lehne.
Future-proofing means investing early and consistently in people. Businesses need to proactively map out their future workforce based on what skills will be needed going forward. This means making smart and strategic employment decisions.
“We see the most sustainable impact when organisations proactively shape their talent ecosystems and foster a culture of continuous learning,” adds Mason.
From talent provider to strategic partner Working at the heart of STEM workforce development and hiring globally, SThree sees firsthand how skilled professionals are bringing AI to life, not just in labs and data centres, but at the heart of business and public services. “We work with clients to help them build a workforce infrastructure that underpins AI innovation. We understand where skill gaps are emerging and how to close them, working with clients to forecast needs, shape workforce strategies and ensure teams are resilient, diverse and ready to scale AI ethically.” says Lehne.
An AI-ready team blends technical acumen with adaptability, communication skills and ethical awareness. While demand for skilled professionals in AI is soaring, roles are changing faster than hiring strategies can adapt, meaning many organisations are finding themselves unprepared for the complexity ahead. SThree aims to help close that gap, offering deep STEM expertise and strategic workforce insight.
“AI adoption isn’t inevitable,” Mason explains. “It’s a choice, and that choice begins with investing in people.”
AI-first startups could add £550 billion1 to the UK economy over the next decade, but only if the compute and connectivity gap is addressed.
These startups rely on high-performance compute and seamless connectivity to develop, train and deploy AI solutions. Without sufficient compute and connectivity, however, AI-first SMEs face barriers to scaling, slower innovation cycles and a weakened international standing.
Building the foundations to scale AI innovation
Digital Catapult is accelerating the practical application of AI across industries, helping AI-first startups turn innovation into commercial success. Accelerator programmes, for example, drive AI adoption across multiple sectors, including the creative industries where AI is driving the rise of ‘CreaTech’ and boosting the UK’s creative output. Closing the compute and connectivity gap will ensure that AI-first startups have the infrastructure they need to scale.
Closing the gap with targeted intervention
This infrastructure includes shared compute environments, open networks and simulation tools that bridge the gap between experimentation and real-world deployment. Digital Twin platforms allow startups to simulate and refine AI-driven systems in real-world environments. This May, the UK Digital Twin Centre opens in Belfast. It offers compute resources to bridge R&D
and commercialisation, supporting the UK Government’s 31-point AI Action Plan to scale safe, effective AI innovation. Digital Catapult also helps close the gap through cutting-edge facilities, innovation programmes and expert consultancy. Our testbeds provide SMEs with access to compute power and open networks, enabling them to develop and scale AI solutions. We also support AI-first SMEs through the Innovate UK BridgeAI programme. Over the past decade, we have facilitated £40 million of investment into CreaTech SMEs, turning bold ideas into commercial success.
Making AI innovation market-ready
Despite the availability of high-performance compute platforms like Isambard 3, CFMS, and the Co-Star Network, many AI-first startups still face barriers moving from R&D to commercialisation. High-cloud compute costs and limited digital support make scaling difficult, highlighting the need to close the compute and connectivity gap further, so startups can market new AI solutions. Targeted intervention will be necessary, pushing the boundaries of AI-driven innovation.
Reference
Enterprises increasingly recognise the transformative potential of agentic AI, but many struggle to turn that promise into real-world impact.
WRITTEN BY Kevin Kiley President, Airia
Akey barrier is the growing problem of AI sprawl — the unchecked spread of disconnected, siloed AI solutions across business functions, creating a landscape of ‘shadow AI.’ This fragmented approach inflates costs, limits scalability and, more critically, creates blind spots in security and governance. These gaps leave organisations vulnerable to both accidental data exposure and malicious attacks.
Orchestrating success through unified control
This is where enterprise AI orchestration platforms like Airia are proving transformative. These platforms provide a unified environment for AI development, deployment and management, helping CIOs regain control over their AI landscape while enabling technical teams to innovate securely and efficiently.
Selecting a platform with comprehensive orchestration capabilities allows organisations to build and deploy secure agentic workflows across different business functions, eliminating the risks associated with shadow AI. Through its secure AI gateway, AI orchestration platforms seamlessly integrate with existing AI agents, enabling organisations to leverage their current AI investments while maintaining centralised control.
Platforms like Airia also have a centralised governance framework built in, ensuring consistent security protocols and compliance standards across all AI implementations while maintaining the agility needed to keep pace with rapid advances in AI models.
Balancing innovation with security
What sets Airia apart is its ability to balance innovation with control. Its intuitive platform streamlines the integration of new AI capabilities while maintaining robust security measures. This empowers technical teams to quickly deploy and scale AI solutions without compromising governance standards, significantly reducing time-to-market for AI initiatives.
As AI adoption accelerates, the need for effective orchestration becomes increasingly critical. Airia is leading this evolution, helping organisations tame AI sprawl while accelerating the real-world impact of their investments. By providing a secure, scalable foundation for agentic AI deployment, Airia is enabling enterprises to fully realise the transformative potential of artificial intelligence.
AI has moved from buzzword to business essential faster than almost anyone predicted. However, as adoption surges, many teams are being asked to build the future with tools they barely understand — or haven’t learned.
This gap between ambition and ability isn’t just about technical skills; it’s about people feeling left behind. In boardrooms and break rooms alike, a familiar question is echoing: Who gets to succeed in the age of AI? The answer, we believe, must be: everyone.
AI belongs to more than engineers
The skills to work with AI can’t be relegated to tech teams alone. Designers, marketers, HR professionals, operations leads — everyone has a stake in how AI shapes their roles. Yet, according to the World Economic Forum, over 60% of workers will require upskilling by 2027, much of it AI-related.
That AI training remains a stumbling block.
According to our recent survey of nearly 400 business leaders across the UK and the US, only 20% of companies in the UK, and only 16% in the US, regularly offer AI training. At General Assembly, we’ve seen firsthand how expanding access to AI skills can shift outcomes for individuals, teams and the broader economy.
“When people across functions understand how to use AI tools responsibly and confidently, it unlocks real, immediate value,” notes Jeffrey Bergin, Chief Learning Officer at General Assembly. “This isn’t just about futureproofing; it’s about improving work today.”
Practical, accessible, responsible AI
The speed of AI adoption has left many employees overwhelmed and undersupported. Our focus is on bringing clarity to a space that too often feels exclusive or intimidating. That starts with practical learning: how to prompt ethically; how to evaluate outputs critically; and how to apply AI in real-world workflows. For example, teaching a marketing team how to use AI to analyse customer sentiment without unintentionally reinforcing bias.
As AI accelerates, so must our collective readiness to use it wisely. Learn how we can keep up and continuously harness the full capabilities of AI today.
“AI isn’t a magic wand; it’s a mirror,” says Jourdan Hathaway, Chief Business Officer at General Assembly. “It reflects the data, assumptions and ethics we bring to it. That’s why training must go beyond tools and speak to values.”
The AI Academy, a programme we launched to help businesses scale AI skills across teams, is designed around that philosophy: practical, role-based skills, taught through a human lens. It’s AI for all. We’ve built pathways for everyone from frontline managers to senior strategists — because AI readiness shouldn’t hinge on your job title or technical background.
Upskilling for a shared future
The future of work shouldn’t be something that just happens. It should be something we build intentionally and inclusively. We’re not alone in this mission. Across industries like technology, healthcare, education and public service, forwardthinking companies and organisations across the globe are aligning around a shared goal of making AI skills a public good, not just a competitive edge. It’s encouraging to see this momentum, and our AI Academy was built to drive even more action. Practical AI training makes people feel more confident and capable in their roles. We’re committed to making AI skills accessible to everyone. Because if we want AI to serve everyone, we must ensure everyone knows how to use it. That starts with investing in people, not just platforms.
Let’s build the future of work together
The future of work shouldn’t be something that just happens. It should be something we build intentionally and inclusively.
This is a rare moment. We have the chance to shape how AI enters our workplaces. Not as a source of fear, but as a tool for growth. The question isn’t whether your teams will use AI. It’s whether they’ll be ready to use it well. Let’s make sure they are.
The fusion of artificial intelligence (AI) and healthcare is not just enhancing existing tools; it’s redefining what medical devices can do. No longer passive instruments, devices are evolving into intelligent aids capable of analysing, adapting and even anticipating clinician or patient needs.
From AI-powered diagnostics that spot diseases before symptoms arise to wearables that alert users to early warning signs, this transformation is accelerating. For the medical device industry, this signals a shift that is no longer just about hardware but also about data, algorithms and connectivity. Devices will be able to learn, analyse and respond in real time.
Smarter, faster diagnostics
AI is revolutionising diagnostics by enabling devices to analyse medical images with speed and accuracy. Algorithms can detect tumours, fractures and other abnormalities early. This helps clinicians make faster, more informed decisions. As these capabilities move into portable devices, diagnostics are becoming more accessible and efficient — especially in remote or underserved regions.
Personalised, adaptive devices
using AI to respond dynamically to patient conditions in real time. This shift supports better outcomes and reduces the need for constant human oversight.
Remote monitoring and predictive care
Wearable and home-use devices equipped with AI are reshaping chronic disease management. By continuously tracking vital signs and detecting anomalies, they enable earlier intervention and help prevent hospitalisations. The demand for connected, predictive technologies is driving innovation across the device landscape.
The demand for connected, predictive technologies is driving innovation across the device landscape.
AI’s ability to interpret complex health data is driving personalised care. Medical devices like insulin pumps, cardiac monitors and neurostimulators are increasingly
The NHS faces mounting pressure from rising chronic disease rates and workforce challenges. Our members have AI-powered healthcare solutions which are emerging as vital tools to address these challenges.
AI to predict problems
HealthNet’s AI platform, AdherePredict, identifies patients at risk of poor adherence by analysing data from disease indication to socioeconomic factors. This enables early interventions, supporting the shift from ‘Diagnose and Treat’ to ‘Predict and Prevent.’
Several NHS Trusts are implementing AdherePredict, promising efficient resource allocation, reduced administrative burden, better remote monitoring and enhanced patient experience. By expanding Clinical Homecare capacity from 800,000 to 6.8 million patients, this technology could
New standards and expectations
With these advancements come new regulatory and technical challenges. Agencies are developing frameworks for adaptive learning systems, supporting manufacturers to prioritise transparency, security and compliance. Success now depends not only on hardware quality, but also on data handling and intelligent functionality.
In this new era, AI is not just enhancing medical devices — it’s redefining their role in care delivery.
dramatically reduce NHS pressure.
AI to support family doctors
Livi addresses increasing GP demand alongside easing administrative pressures. With 1 in 20 patients waiting four weeks for GP appointments, their digital solution is transforming service delivery. Currently exploring UK AI rollout after success in Sweden, Livi’s technology bridges physical and digital healthcare, guiding patients to appropriate care settings while reducing administrative tasks. Their AI combines clinical decision support with administrative automation.
The impact in Sweden: 40% reduction in administration time, potentially translating to 100,000 clinical hours annually and higher clinician satisfaction. These AI innovations create a more resilient healthcare system where clinicians can focus on patient care while expanding access and reducing pressure on NHS resources.
From diagnostics to monitoring and treatment support, AI is enhancing how care is delivered and how patients experience it.
The AI-driven medical device boom
The role of AI in medical devices has grown dramatically. A recent BCG report noted that FDA authorisations for AI and machine learning-enabled medical devices have increased more than 35-fold since 2015. By the end of 2023, over 1,000 such devices had been approved. Signalling a clear shift toward more intelligent, data-driven care solutions.
Robotic surgery, for example, is an area seeing rapid development. AI-enhanced tools offer real-time navigation, precision and personalised planning. Transforming orthopaedics and neurosurgery, these AI-integrated systems are increasingly paired with augmented reality overlays and predictive models. As capabilities grow, they promise safer, faster procedures tailored to each patient’s anatomy and clinical context.
Technologies like digital twins will enable real-time simulation of devices and treatment plans.
Smart support for ageing populations
One of AI’s most profound contributions is empowering seniors to live independently. We partnered with a robotics innovator to develop the next generation of household robotic assistants that combine physical support with AI-driven health insights. These assistive devices handle daily tasks and medication reminders while monitoring health signals to flag early warning signs. Designed through behavioural engineering and human-machine interaction workshops, they prioritise intuitive use and real-world benefit over force-fitting technology into people’s lives. By sharing relevant data with care teams, these devices reduce hospitalisations and caregiver burden while preserving patient dignity.
Transforming patient monitoring and health data integration
Remote patient monitoring is another area primed to benefit from AI. We collaborated with a healthtech provider to integrate machine learning into a mobile health platform, enabling real-time analysis of patient-generated data from wearables, apps and connected devices.
Artificial intelligence (AI) in healthcare is no longer a futuristic concept; it is an active force reshaping patient care through its integration with medical devices.
Using predictive models alongside this data to detect anomalies, the platform empowers clinicians to act early and with greater precision. Our team reimagined the interface for both patients and providers, increasing adherence and data accuracy. It reflected what we see as a broader industry trend: transitioning from episodic care to continuous, insights-driven support.
Smarter quality management for safer medical devices
In patient care, compliance complexity grows exponentially as innovation accelerates. Understanding this, we supported a medical device quality management platform in modernising its infrastructure using modular design and the Strangler architecture pattern. This enabled ongoing updates without disrupting clinical use. We developed an independent, AI-powered risk management module that automates hazard identification and traceability throughout the product lifecycle. This not only enhances safety and transparency today but also keeps an eye on tomorrow, as we’ve seen regulators increasingly focus on lifecycle oversight for AI/ ML-enabled devices.
Overcoming challenges in AI-enabled care
Regulatory pressures aren’t the only challenges to consider; concerns about data privacy, cybersecurity, algorithmic bias and transparency must be addressed carefully. At HTEC, we prioritise ethical design principles, build robust security frameworks and align with regulatory standards such as HL7, IHE and FDA guidelines.
Crucially, we believe that AI should augment the clinician’s role, not replace it. Medical devices must support decision-making rather than take it over. The human connection in care remains essential.
Future of seamless, intelligent patient care
The future of AI in patient care will be defined by convergence. Technologies like digital twins will enable real-time simulation of devices and treatment plans. AI-enabled diagnostic platforms will enhance precision medicine. Unified data ecosystems will break silos to create seamless, end-to-end care journeys. Remote monitoring will reduce readmissions and enhance access for underserved communities.
A significant share of successful AI adoption lies in cultural change, clinician training and patient trust. These are areas that require just as much innovation as the algorithms themselves. International collaboration will be key to ensuring equitable innovation and consistent safety standards. We’re already building toward this future. Our focus is on creating AI-powered devices that not only meet today’s clinical needs but also anticipate tomorrow’s possibilities.
Fintech is redefining customer engagement in banking, enabling seamless experiences through AI, gamification and strategic partnerships for sustainable growth.
From AI-driven personalisation to blockchain security, fintech has continuously pushed boundaries, making banking more accessible, efficient and customer-centric.
Enhancing customer experiences in fintech
The rise of mobile banking, open banking and embedded finance has reshaped the industry, creating new opportunities for collaboration between fintech startups and legacy institutions. As technology continues to advance, the sector will only continue evolving.
“It’s no longer just about apps or websites, it’s about consistency across touchpoints,” highlights Devie. From seamless app-to-branch experiences to leveraging generative AI for real-time support, banks are adopting fintech strategies to deliver frictionless engagement.
Gamification is another key trend improving the area. “Banks are acquiring gaming platforms to boost engagement, helping customers save, invest and reduce debt in a personalised way,” explains Devie.
Collaboration and cultural alignment Fintech-bank partnerships are key to digital transformation but can be difficult to navigate. “Aligning cultural values is a major hurdle,” offers Devie. She highlights three common approaches: acquisition, creating innovation hubs and partnerships through mentorship or investment.
“While acquisitions often face integration issues, innovation hubs and partnerships are proving more effective for fostering sustainable solutions.” As in all areas of digital transformation within the financial landscape, regulatory alignment remains essential.
“Regulators, like the FCA in the UK, are fostering innovation with sandboxes to test fintech solutions,”
notes Devie. The sandbox is used as a mechanism for bringing startups into the ecosystem, observing them, taking lessons and feeding useful data back to the banks. This evolving regulatory mindset is enabling banks to innovate responsibly while adhering to ever-evolving compliance standards.
The future of banking transformation As innovations from fintechs continue to blur the lines between traditional and digital banking, Devie emphasises the importance of sustainable growth.
“Scaling fintech solutions requires long-term thinking, combining agility with regulatory foresight to ensure solutions remain impactful,” stresses Devie. “As we move forward, we’ll see banks and fintechs looking more alike, driving innovation and growth in unison.”
In the next decade, the fusion of fintech agility with the strengths provided by traditional banks has the power to transform the industry, redefining customer experiences and reshaping the financial ecosystem.
Join over 2,500 attendees in June 2025 for an unmissable agenda of panel discussions, presentations, roundtables and networking at the Financial Transformation Summit (ftsummit.net)
WRITTEN BY
Emma Storr
Content Marketing Manager, MoneyNext
The fintech sector is already well-versed in harnessing AI to improve financial services, including how we detect fraud, assess creditworthiness and personalise financial services.
Artificial intelligence is set to further transform financial services, with fintech innovators and entrepreneurs — already skilled at leveraging technology to boost efficiency, cut costs and improve user outcomes — at the forefront.
Fintech drives inclusive economic growth
UK fintech has consistently had a positive impact on the economy and consumers nationally. According to research from Vested Impact and Accenture, 98% of UK fintechs directly boost economic productivity and growth — through job creation, supporting enterprise and expanding access to financial services. Moreover, 39% of UK fintechs are actively reducing financial inequality, improving access for underserved communities and boosting financial literacy. According to the British Business Bank, nearly 60% of all SME lending across the UK is done by fintech.
The sector’s economic strength reinforces this momentum. According to Data City, fintech contributes £8.3 billion in Gross Value Added (GVA) to the UK economy, with productivity 60% higher than the national average. GVA per employee in fintech is 1.5 times the UK average; and with a 14.2% annual growth rate, employment within the sector is set to rise from 82,800 to over 109,000 within two years.
AI-driven UK fintech leadership
BY
WRITTEN
Devie Mohan Founder and CEO, Burnmark
It is these innovative, forward-thinking fintech firms that will continue to use AI to drive a better financial sector. For instance, AI is proving to be one of our strongest tools against financial crime. Many UK fintechs are leveraging AI-powered network intelligence to detect fraud and money laundering; others are using machine learning to spot suspicious behaviour patterns in real time, protecting consumers and institutions alike. Earlier this year, the UK Prime Minister set out ambitions to make the UK a world leader in AI. The UK is already a world leader in fintech, securing more investment and boasting more fintech unicorns than anywhere else, bar the US. With increasing unpredictability in the US, the UK has a unique opportunity. Our UK Government, regulators and industry must work together to cement our global fintech leadership, which will bolster our UK leadership in AI.
Most established financial institutions face the same significant challenge: moving beyond treating AI as merely an efficiency driver.
AI as the strategic core in finance
Technology has always played a pivotal role in banking and insurance. The rapid acceleration of AI capabilities is fundamentally re-shaping how financial institutions serve customers and structure their operations.
providers. This new standard for digital engagement means institutions must deliver intuitive, conversational interfaces, proactive financial guidance and highly tailored interactions.
HTEC’s AI solutions have responded to this shift. Internal success surveys found that for one customer in tech protection insurance, our solutions achieved 60% faster claims resolution, 30% faster subscriber onboarding and 99.9% system uptime. These are critical metrics for an industry where customer trust depends on reliability and responsiveness. The result isn’t just cost savings; it’s enhanced service quality and the ability to reach previously underserved markets. Similarly, for a major payment processor, we achieved a 50% reduction in processing time, with over $5 billion processed in the first two years.
The legacy approach of spending 70% of IT budgets1 on ‘keeping the lights on’ is giving way to a new paradigm where AI forms the backbone of enterprise strategy, enabling entirely new capabilities in product design, service delivery and business model evolution.
This shift demands a rethinking of AI’s role as the central organising principle for modern financial institutions. The opportunity lies in orchestrating intelligent, adaptive systems that learn and evolve across the enterprise.
At HTEC, we’ve seen firsthand how AI-first solutions can offer a transformative path forward. Rather than simply layering new technology onto legacy systems, forward-thinking institutions are using AI to fundamentally reimagine their customer journeys and operational models.
Forward-thinking institutions are using AI to fundamentally reimagine their customer journeys and operational models.
Agentic AI unlocks value from all data
The most forward-thinking institutions are using AI to extract value across both structured and unstructured data sources. By processing everything from transaction records to client communications and market signals, these intelligent systems continuously learn, reason across domains and autonomously take action.
In one financial workflow platform modernisation project, this approach accelerated user registration by 400% and achieved perfect 10/10 stakeholder satisfaction. For another client, it enabled a reduction in integration timelines from eight weeks to three days while cutting mapping effort by 80%. These are tangible examples of AI’s transformative power when applied across data types.
Customer expectations redefined by genAI
As consumers grow accustomed to AI-powered, personalised digital experiences in other industries, they now expect the same from their financial services
End-to-end transformation requires a holistic approach Successful AI transformation spans the full technology and business stack, from model development and process redesign to responsible AI governance and change management. The challenge is clear: how to scale AI responsibly while meeting intensifying regulatory demands and ethical obligations.
For a banking-as-a-service provider, our holistic approach to navigating complex Payment Card Industry Data Security Standard (PCI DSS) requirements while implementing AI systems resulted in $100,000 annual cloud savings and 50% fewer support tickets, according to another user success survey. This demonstrates that compliance can be a business enabler rather than merely a cost centre.
Strategic AI adoption in finance
For financial services leaders, the question is no longer whether to implement AI, but how to do so strategically while managing legacy constraints. The organisations gaining a competitive advantage are taking a three-pronged approach:
1. Prioritising high-impact use cases that deliver tangible business value
2. Implementing a data infrastructure that can support advanced AI applications
3. Developing talent strategies that blend financial expertise with AI capabilities
The financial institutions thriving in this new landscape aren’t necessarily those with the largest technology budgets. Rather, they’re the ones most effectively bridging the gap between customer needs, operational realities and technological possibilities.
Reference
1. Woollacott, E. 2025. IT Pro. Banks are persisting with the ‘patch and upgrade’ approach to legacy systems – and it’s swallowing up IT budgets.
WRITTEN BY Francesca Rossi
IBM Fellow and AI Ethics Global Leader, AAAI
As artificial intelligence capabilities evolve rapidly, the field of AI research is undergoing a major transformation—reshaping its topics, methods, and community structures alike.
As AI capabilities evolve rapidly, AI research is also undergoing a fast and significant transformation along many dimensions, including its topics, methods, research community, and working environment. Topics like AI reasoning and agentic AI have been studied for decades but now have an expanded scope considering current AI capabilities and limitations. AI ethics and safety, AI for social good, and sustainable AI have become central themes in major AI conferences. Moreover, research on AI algorithms and software systems is becoming increasingly tied to substantial amounts of dedicated AI hardware, notably GPUs, leading to AI architecture co-creation, in a way that is more prominent now than over the last three decades.
Corporate influence and the changing research landscape
Related to this shift, more AI researchers work in corporate environments, where the necessary hardware and other resources are more easily available, compared to academia, questioning the roles of academic AI research, student retention, and faculty recruiting. The pervasive use of AI in our daily lives and its impact on people, society, and the environment makes AI a sociotechnical field of study, highlighting the need for AI researchers to work with experts from other disciplines, like psychologists, sociologists, philosophers and economists.
The growing focus on emergent AI behaviors rather than on designed and validated properties of AI systems renders principled empirical evaluation more important than ever. Hence
the need arises for well-designed benchmarks, test methodologies, and sound processes to infer conclusions from the results of computational experiments.
Legacy and social media increasingly cover AI research advancements, often with contradictory statements.
Why AI’s rapid expansion needs global coordination
The exponentially increasing quantity of AI research publications and the speed of AI innovation are testing the resilience of the peer-review system, with the immediate release of papers without peer-review evaluation having become widely accepted across many areas of AI research.
Legacy and social media increasingly cover AI research advancements, often with contradictory statements that confuse the readers and blur the line between reality and perception of AI capabilities. All this is happening in a geo-political environment, in which companies and countries compete fiercely and globally to lead the AI race. This rivalry may impact access to research results and infrastructure as well as global governance efforts, underscoring the need for international cooperation in AI research and innovation.
next wave will reshape industries and
In 2025 and beyond, AI’s evolution is going to continue with mind-boggling pace and complexity, influenced by both technological advancements and geopolitical shifts.
The integration of AI with quantum computing and advancements in reasoning will enhance its capabilities, reduce its environmental impact and profoundly reshape industries. How? By automating complex tasks, enhancing decision-making and driving innovation.
The real-world impact of AI
For instance, in healthcare, AI will accelerate drug discovery, improve diagnostics and personalise treatment plans, potentially reducing clinical trial costs by up to 70% and shortening timelines by as much as 80%.* This is a gamechanger when the current process takes roughly a decade.
In manufacturing, AI-powered predictive maintenance will reduce downtime and optimise production efficiency. We will see AI pushing the boundaries of what is possible, enabling the development of autonomous vehicles and humanoid robots. Additionally, it will challenge traditional norms by redefining work roles, with AI agents increasingly handling tasks that require human-like intelligence, such as customer service and content creation.
AI concerns and how to address them
On the flip side of this, there are concerns around how this could destabilise the workforce (and how individuals will then need to be upskilled sooner rather than later to utilise AI to its fullest), shared by some of the biggest tech leaders in the world, including Bill Gates, Sam Altman and Mustafa Suleyman.
These developments also underscore the need for robust regulatory frameworks and ethical considerations to ensure that AI benefits humanity without exacerbating existing inequalities. The future of AI demands a holistic approach by the entire ecosystem — academics, governments, businesses and NGOs — that balances innovation with responsibility.
Reference
*Twilio Segment, 2023. The State of Personalization 2023.
Agencies are developing frameworks for adaptive learning systems, supporting manufacturers to prioritise transparency, security and compliance.
~Andrew Davies, Executive Director Digital Health, ABHI
As the UK Government rolls out its ambitious AI Opportunities Action Plan, central and local authorities are pioneering ethical AI to reshape services, from central government policy to frontline council operations.
The AI Opportunities Action Plan, launched in 2025, aims to make the UK a global leader in responsible AI, backed by a £14 billion investment and 50 strategic recommendations for public services.
The AI playbook
The UK’s AI transformation is being driven by the Department for Science, Innovation and Technology’s (DSIT) 10-principle playbook. The framework mandates ethical deployment with human oversight across critical citizen services. All departments must follow Algorithmic Transparency Recording Standards while over 1 million civil servants receive AI training. Current implementations include GOV. UK’s AI chat function and Crown Commercial Service (CCS) procurement tools — all operating within strict safeguards.
initiatives align with the national plan’s goal to ‘boost productivity by 1.5% annually,’ demonstrating how community-driven AI solutions can pave the way for nationwide impact.
Generative AI may be the breakthrough small businesses have long needed. Frontier technologies are often out of reach for smaller firms, but the real shift lies in natural language queries. The ability to interact with tools like ChatGPT, Claude or Gemini as easily as chatting at the local pub is game-changing.
These protective measures keep citizen welfare at the heart of technological advancement.
The Government’s unwavering commitment to Principle 2 of the AI Playbook (‘Use AI lawfully, ethically and responsibly’) is demonstrated through concrete safeguards across critical services. The NHS ensures all AI-generated cancer screenings undergo rigorous human validation while the DWP implements continuous monitoring to eliminate bias in welfare eligibility algorithms. ‘AI must serve people, not the other way around,’ emphasises Minister Feryal Clark, underscoring how these protective measures keep citizen welfare at the heart of technological advancement.
Local innovation: Camden and Newham lead the way
At a local level, councils are proving AI’s transformative potential; from Camden’s AI Campus, where Google DeepMind trains underrepresented students, to Newham’s Centre for AI, officially launched at the 2024 DigiGov Expo, which tackles housing shortages, social care pressures and climate challenges through predictive modelling. These
The DigiGov Expo (24–25 September) has introduced a specialised ‘AI Theatre’ to examine approaches to AI implementation across government, including infrastructure development and local service applications while facilitating discussion between government and technology suppliers on practical challenges. With £47 billion in projected annual economic gains, the UK’s AI future hinges on this dual approach: national ambition grounded in local experimentation.
As an entrepreneur at the “2025 OECD Digital for SMEs Roundtable” in Paris put it: “thanks to Generative AI, I can focus more on what I love to do, without needing to know the first thing about coding”.
Any business, no matter how small, can now delegate cognitive tasks to advanced AI models — simply by asking. However, while basic uses are accessible, higher-impact applications like agentic AI demand new skills and deeper understanding.
AI adoption across business AI adoption is growing across the OECD. Between 2023 and 2024, the share of small businesses using AI rose from 7% to 12%. Medium-sized firms increased from 12–20%, and large businesses from 29–39%.
The “2025 OECD D4SME survey”, — covering SMEs on digital platforms in 10 OECD countries — shows that 26% now use Generative AI, up from 18% a year earlier. Of these, 91% report efficiency gains and 76% highlight greater innovation.
Embracing new tools
Still, many SMEs remain hesitant. Among those not using Generative AI, 67% cite uncertainty about its risks and uses, and 83% express data privacy concerns. Other barriers include maintenance costs (40%), lack of time for training (39%) and hardware expenses (32%).
Digitally mature SMEs are more likely to adopt AI. The OECD survey shows 61% adoption among those with advanced digital practices, compared with just 25% among businesses using only email and office software. Younger leadership matters too — SMEs led by CEOs under 45 are more likely to embrace AI.
Governments across the OECD, G7 and beyond are closely watching the risks and opportunities. Generative AI could unlock major productivity gains for SMEs — but bridging the gap between promise and practice will require co-ordinated support and action.
Today, generative AI is already transforming the way we live and do business through a multitude of use cases, from human-like chatbots to improving productivity. Next, we are moving to AI-powered agents that make decisions and even transact autonomously on our behalf.
Over the past few years, AI has become a focal point for investors, businesses, regulators and the general public, thanks to the rapid adoption and mainstream application of transformer-based models like ChatGPT. As more powerful models and applications emerge, AI is set to revolutionise commerce by enabling agentic transactions, where AI autonomously makes decisions and transacts on our behalf.
Currently, AI apps and agents support the user to the recommendation or listing stage when looking to buy goods or services through their interface. We are witnessing the first steps into enabling autonomous checkouts. Visa Intelligence Commerce is at the forefront of this transformation, providing developers with tools to create personalised and secure shopping experiences, including the checkout journey.
How AI agents can reshape commerce
Most agents are currently deployed to execute tasks related to internal operations. However, the trend is shifting towards using agentic AI in customer-facing applications, especially in commerce. While purchase recommendations are common, autonomous checkouts are still rare. Existing payment infrastructure, standards, rules, compliance and customer journeys will need to adapt to enable these new autonomous commerce and payment experiences, as most current experiences and processes are designed as human-centric systems. Agents will require set limits at the workflow or agent level, explicit permissioning and a robust identity framework. The level of autonomy of these systems in purchasing on our behalf will evolve alongside customer trust, orchestrating models’ intelligence and ecosystem enablement.
on transaction value, count and vetted merchants and categories, plus apps.
In the final phase, ‘AI Orchestrates,’ advanced agents will manage complex workflows with little human intervention. These agents will execute payments with mid to high levels of autonomy under continuous automated monitoring and audit mechanisms. AI agents will require an assigned budget; access to payment credentials; and an identification system. We are currently in the ‘AI initiates’ phase.
Architecting the future of AI-powered commerce
Agents will execute payments with mid to high levels of autonomy.
We strongly believe that maintaining the right balance between AI automation and human-in-the-loop will be key for a secure AI-powered commerce experience. User control, even in an autonomous environment, is key. We are working to architect the future securely with Visa Intelligent Commerce. We are leveraging our 30-year experience in AI to fight fraud and risk, as well as being at the forefront of secure ecommerce through tokenisation.
At Visa Consulting and Analytics, we foresee three potential distinct phases in the adoption of agentic commerce. In the first phase, ‘AI Initiates,’ AI interacts with ecommerce sites and narrows on relevant personalised recommendations with the potential to initiate a checkout process. However, purchases need to be actively confirmed by the user and payments authorised on a one-by-one basis. In the second phase, ‘AI Transacts,’ AI agents will be able to purchase on our behalf and execute payments for low-risk transactions. Payers will grant limited autonomy to these systems by setting limits
Visa Consulting and Analytics collaborates with partners (issuers, acquirers, PSPs and merchants) to envision, plan and implement innovative experiences for the next wave of commerce. Examples include a marketing agent that monitors keyword pricing and purchases ad campaigns autonomously; a logistics agent that autonomously schedules maintenance and arranges payments to the auto-shop ensuring minimum downtime; an AI-powered 3D design software that buys 3D assets by itself to achieve a set goal; or a concierge agent that plans complete birthday parties based on themes and family preferences.
The future of AI is exciting, transformational, AI-powered, but human-centric — and is already here.
An AI-powered building management platform is making real estate portfolios smarter, greener and more efficient.
The rapid acceleration of AI is having a transformative impact on numerous industries. One particular area where AI’s influence is gaining momentum is the built environment. Jean-Simon Venne, Co-founder and CTO at BrainBox AI, explains: “AI has matured from experimental applications focused primarily on energy optimisation, predictive maintenance, and basic automation. It is now a core operational layer of building maintenance being fully integrated into building platforms.”
AI for building operations efficiency
From its humble debut in buildings as a nascent application, AI has evolved into a strategic enabler of smart and net-zero buildings. BrainBox AI has been a leader in this industry shift with its autonomous AI for heating, ventilation and air conditioning (HVAC) systems as well as its generative AI-driven virtual building engineer, ARIA, both of which have been recognised by TIME Magazine as Best Inventions of the year.
Clients using the company’s AI-powered HVAC solution — such as Dollar Tree and Cammeby’s International Group — have reported significant, measurable reductions in both energy costs and carbon emissions. At Cammeby’s office tower in New York City, HVAC energy consumption dropped by 15.8%, accompanied by a 16.1% reduction in related carbon emissions. Meanwhile, Dollar Tree reported total energy savings of over US$1 million across 616 of its locations. AI is also playing a vital role in addressing the growing shortage of qualified facility managers and technicians. As teams shrink and legacy HVAC systems age, maintenance backlogs continue to grow — compounded by increasing pressure to meet sustainability and energy efficiency targets. Agentic AI solutions, such as ARIA, help bridge these gaps, empowering facility managers to do more with fewer resources.
Future-proofing industry assets
As AI and IoT technologies continue to evolve, those who embrace innovation will be better equipped to meet rising expectations, drive sustainability and secure longterm value by strengthening their operations.
Venne concludes: “We embrace the future with AI at the helm because it is incredibly exciting. Traditional approaches simply can’t keep up with the complexity and pace of today’s demands.” Adopting AI is not just about staying competitive; it’s about ensuring operational resilience and future-proofing assets in a rapidly changing industry.
AI is rapidly transforming the business landscape, yet over half of CEOs identify new technologies or generative AI as one of their three greatest workplace challenges.1
Phillippa LennoxKing Head of
Artificial intelligence offers unprecedented opportunities to enhance sustainability and responsible practices. However, it also presents significant challenges that organisations must navigate carefully.
Opportunities presented through AI use
AI can help eliminate unconscious bias in recruitment and career development by analysing resumes without gender or racial prejudices and supporting personal development plans. In agriculture, AI reduces waste by aiding in efficient resource utilisation. In energy sectors, it helps balance grids and predict demand, leading to optimised energy consumption and lower carbon footprints. In healthcare, AI assists with diagnosis and treatment recommendations, analysing extensive genetic and biological data to accelerate the development of new medicines and vaccines and improve patient outcomes.2
Risks of irresponsible AI use
• Bias and inequality: If not designed responsibly, AI systems can perpetuate existing biases, reflecting historical inequalities. Businesses must use diverse, high-quality datasets, conduct regular audits and maintain human oversight by diverse stakeholders to effectively mitigate this risk.
• Environmental impact: Data centres account for 0.5% of combustion emissions, which could increase by up to 80% by 2030.3 A single search on a generative AI platform uses around 10 times more energy than a Google search.4
• Workforce displacement: The rise of automation and AI-driven systems could lead to job displacement, social isolation and increased inequality. Companies need to focus on creating AI applications that prioritise workers’ wellbeing, including upskilling programmes to narrow the digital divide.
The path forward
To harness AI’s potential responsibly, businesses must adopt a values-led approach to AI implementation, developing transparent, holistic and ethical AI strategies that consider broader social and environmental impacts, aligned with the organisation’s core purpose. By proactively addressing the challenges and embracing the opportunities, organisations can ensure that AI serves as a force for good, driving innovation while upholding the principles of responsible business and sustainability.
References
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